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024 8  0636920430933 
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041 0  eng 
100 0  O'Reilly Media, Inc.,|eauthor. 
245 10 O'Reilly Strata Data and AI Superstream|h[O'Reilly 
       electronic resource] /|cO'Reilly Media, Inc.. 
250    1st edition 
264  1 |bO'Reilly Media, Inc.,|c2020. 
300    1 online resource (1 video file, approximately 7 hr., 50 
       min.) 
336    two-dimensional moving image|btdi|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
347    video file 
365    |b4000.00 
520    You'll get access to O'Reilly data and AI experts. Deep 
       dives into some of the hottest topics in the industry. 
       Intriguing case studies. And a chance to try out new 
       technologies in a live coding environment-all without 
       stepping onto a plane. Day One ML in Production You've 
       built a cool model and you want to get it in front of 
       users. Whether you need to break free of Jupyter Notebooks,
       resolve problems that plague a majority of machine 
       learning projects, or deploy machine learning models and 
       applications to the cloud, these sessions offer a variety 
       of strategies and practices from top companies for 
       deploying machine learning projects in production. Day Two
       Streaming Data Stream processing is key to data 
       integration, as companies must efficiently and effectively
       process and analyze growing amounts of data in real time. 
       The architecture, features, and capabilities of tools like
       Spark, Flink, Kafka, Pulsar, and Ray help businesses grow 
       and thrive at a faster pace. These sessions explore 
       streaming and real-time data and how to store, scale, and 
       analyze this gold mine of information. What you'll learn-
       and how you can apply it Day One features content on 
       Machine Learning in Production. We will cover the 
       following: MLOps with Jenkins and Prometheus MLFlow and 
       Kubeflow fundamentals Optimizing ML for production Day Two
       features content on Streaming Data. We will cover the 
       following: Apache Spark on Kubernetes Digital Twins A Lyft
       case study Batch and stream processing with Apache Beam 
       This Superstream is for you because... You'll fast-track 
       career-boosting skills with this event via technical 
       sessions and interactive Katacoda training. Prerequisites:
       An understanding of data science and machine learning 
       fundamentals. About your hosts Alistair Croll is a best-
       selling author specializing in technology and business 
       strategy. He co-founded Coradiant (acquired by BMC in 
       2011) and helped launch Rednod, CloudOps, Bitcurrent, Year
       One Labs, and other early-stage companies. He works with 
       startups on business acceleration and advises companies on
       innovation and technology. Alistair tries to mitigate 
       chronic ADD by writing about far too many things at Solve 
       For Interesting. Rachel Roumeliotis, vice president of 
       content strategy at O'Reilly, leads an editorial team that
       covers a wide variety of topics ranging from full-stack to
       open source in the enterprise to emerging programming 
       languages. She's a program chair of O'Reilly's OSCON, 
       TensorFlow World, and Strata Dat... 
533    Electronic reproduction.|bBoston, MA :|cSafari,|nAvailable
       via World Wide Web. 
538    Mode of access: World Wide Web. 
542    |fCopyright © O'Reilly Media, Inc. 
550    Made available through: Safari, an O'Reilly Media Company.
588 00 Online resource; Title from title screen (viewed March 17,
       2020) 
655  7 Electronic videos.|2local 
700 1  Jain, Shubhankar,|eauthor. 
700 1  Yang, Jin,|eauthor. 
700 1  Vartak, Manasi,|eauthor. 
700 1  Fregly, Chris,|eauthor. 
700 1  Shao, Liqun,|eauthor. 
700 1  Wahner, Kai,|eauthor. 
700 1  Nielsen, Dave,|eauthor. 
700 1  Wylde, Micah,|eauthor. 
700 1  Bennett, Austin,|eauthor. 
710 2  Safari, an O'Reilly Media Company. 
856 40 |zConnect to this resource online|uhttps://
       ezproxy.naperville-lib.org/login?url=https://
       learning.oreilly.com/library/view/-/0636920430933/?ar